This Specialization equips learners with practical, job-ready skills in predictive analytics and machine learning using R. Beginning with statistical modeling and data visualization, learners progressively build expertise in association rule mining, classification modeling, churn prediction, and customer behavior analytics. Through hands-on, industry-relevant projects in retail, finance, and telecom domains, learners gain experience preparing data, engineering features, training models, and evaluating performance using real-world datasets. By the end of the program, learners will confidently apply R to solve business problems, interpret analytical results, and support data-driven decision-making across multiple industries.
Applied Learning Project
Learners complete hands-on projects using real-world datasets from retail, finance, insurance, and telecom industries. Projects include building predictive models, performing market basket analysis, evaluating classification performance, and preparing churn datasets for machine learning. Each project mirrors authentic industry workflows, enabling learners to apply R programming and analytics skills to solve practical business challenges.
